title: Site-specific data confirm arsenic exposure predicted by the U.S. Environmental Protection Agency.
abstract: The EPA uses an exposure assessment model to estimate daily intake to chemicals of potential concern. At the Anaconda Superfund site in Montana, the EPA exposure assessment model was used to predict total and speciated urinary arsenic concentrations. Predicted concentrations were then compared to concentrations measured in children living near the site. When site-specific information on concentrations of arsenic in soil, interior dust, and diet, site-specific ingestion rates, and arsenic absorption rates were used, measured and predicted urinary arsenic concentrations were in reasonable agreement. The central tendency exposure assessment model successfully described the measured urinary arsenic concentration for the majority of children at the site. The reasonable maximum exposure assessment model successfully identified the uppermost exposed population. While the agreement between measured and predicted urinary arsenic is good, it is not exact. The variables that were identified which influenced agreement included soil and dust sample collection methodology, daily urinary volume, soil ingestion rate, and the ability to define the exposure unit. The concentration of arsenic in food affected agreement between measured and predicted total urinary arsenic, but was not considered when comparing measured and predicted speciated urinary arsenic. Speciated urinary arsenic is the recommended biomarker for recent inorganic arsenic exposure. By using site-specific data in the exposure assessment model, predicted risks from exposure to arsenic were less than predicted risks would have been if the EPA's default values had been used in the exposure assessment model. This difference resulted in reduced magnitude and cost of remediation while still protecting human health.
authors.affiliation: AGEISS Environmental, Inc., Denver, CO 80202, USA.
authors.forename: S
authors.initials: S
authors.lastname: Walker
authors.forename: S
authors.initials: S
authors.lastname: Griffin
mesh_terms: D000465:Algorithms; D001151:Arsenic / Q000032:analysis* / Q000652:urine; D001682:Biological Availability; D004391:Dust / Q000032:analysis; D004781:Environmental Exposure / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D012989:Soil Pollutants / Q000032:analysis; D014481:United States; D014484:United States Environmental Protection Agency
chemical_list: D004391:Dust; D012989:Soil Pollutants; D001151:Arsenic